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GPU compute for AI, machine learning and more

GPU

On-demand GPUs for parallel processing workloads such as machine learning, scientific computing, and video processing.

GPU compute for AI, machine learning and more

GPU

On-demand GPUs for parallel processing workloads such as machine learning, scientific computing, and video processing.

GPU

Scientists, artists, and engineers need access to significant parallel computational power. Offering GPU-optimized virtual machines accelerated by the NVIDIA Quadro RTX 6000, harnessing the power of CUDA, Tensor, and RT cores to execute complex processing, deep learning, and ray tracing workloads.


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On-demand GPU

Between purchasing, installing, and maintaining GPUs, the cost of ownership is often high. Leverage the power of GPUs while benefiting from the main value proposition of cloud: turning a capital expense into an operating expense.

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Market Leading Hardware

GPUs are NVIDIA Quadro RTX 6000 units, currently considered one of the best in market GPUs. With CUDA, Tensor, and RT cores in each unit, these GPUs support any use cases associated with parallel processing, deep learning, or ray tracing.

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Simplifying Complex Use Cases

You focus on your core competencies, we’ll worry about the hardware that makes them possible. Cloud GPUs remove the barrier of entry for complex use cases such as machine learning, AI, and video streaming.

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Multiple Plan Types

One GPU card isn’t enough for your projected workloads? Not a problem. GPU plans offer up to four cards per instance, depending on how much horsepower you need.

Specifications

Technical Specifications

Free Bundled Services

Complementary Paid Services

Recommended Workloads

  • Accelerated data science models
  • Machine learning applications
  • Artificial intelligence analysis
  • Parallel processing workloads
  • 3D modeling and design applications

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Cloud GPU Overview

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Quadro RTX 6000 Specs

CUDA Cores (Parallel-Processing) 4,608
Tensor Cores (Machine & Deep Learning) 576
RT Cores (Ray Tracing) 72
GPU Memory 24 GB GDDR6
RTX-OPS 84T
Rays Cast 10 Giga Rays / Sec
FP32 Performance 16.3 TFLOPS

Particle Physics Performance Per Dollar

GPU Benchmark Report Animated Graph (2)

Dedicated + RTX6000 GPU Plans

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$ /mo
RAM CPUs SSD Storage GPU Cards Transfer Network In Network Out Monthly Hourly
32 GB 8 640 GB 1 16 TB 40 Gbps 10 Gbps $1,000 $1.50
64 GB 16 1280 GB 2 20 TB 40 Gbps 10 Gbps $2,000 $3.00
96 GB 20 1920 GB 3 20 TB 40 Gbps 10 Gbps $3,000 $4.50
128 GB 24 2560 GB 4 20 TB 40 Gbps 10 Gbps $4,000 $6.00

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